The emergence of the industrial internet is yielding a host of energy efficiency opportunities. Key to realising this potential is not only gathering data – just as important is timely analysis and presentation in a format that enables businesses to draw effective and relevant conclusions. Recognising this, key players are launching applications and services that enable businesses to take advantage of big data to boost industrial and commercial efficiency. David Appleyard explores this changing data landscape.
Though still in relative infancy, the industrial internet represents an opportunity for fundamental change within the industrial and commercial sectors of the global economy.
Indeed, McKinsey Global Institute has previously estimated an annual economic impact from the use of this widespread connectivity at $2.7 trillion to $6.2 trillion by 2025.
With the value proposition becoming clear, pace in the development of appropriate tools to exploit this data more effectively is accelerating.
GE’s Rolf Gibbels, Head of global sales and strategy for GE’s Power Digital Solutions group, explains the new strategic direction in the industrial data environment, “The industry has been collecting huge amounts of data in their plants and facility equipment, including sensors, SCADA systems, and historical data.”
Certainly there are thousands of sensors on a typical power plant, gathering quadrillions of bytes of data per year. But, as Gibbels adds: “What we have seen is that the use of it has been fairly minimal in terms of analysing your data. Maybe only 2% of any data was really effectively analysed and the rest almost wasted.”
All that is changing though. Gibbels notes: “In general, the industry is focused on leveraging big data and data more effectively, making connections between performance, market requirements and market conditions. In order now to analyse and effectively manage everything in context, analytics – big data – becomes extremely important.”
The key to effective use of this data is that it enables more advanced insight into plant and asset performance and therefore the management and understanding of machine and equipment health. Clearly such insights can boost the reliability of plant systems and allow further optimisation of management and maintenance programmes, as well as presenting opportunities to improve process efficiency.
Gibbels: “To make more use of this data from a predictability standpoint is obviously more critical. The more you understand your data, the more effectively you can run your plants which can potentially help you stay more competitive in increasingly unregulated markets.”
He observes: “There’s definitely a lot more use to be had from this data than a lot of sites currently think or are maybe even able to do. A key element is really to give a clear insight into this data. Often it’s about clear visualisation of the information so that you can make some intelligent decisions from it.”
The push for more effective data visualisation has prompted some of the industrial sector’s biggest players to launch products that support use of big data among their customers. For example, Emerson Industrial Automation recently launched its Energy Savings Advisor, a web-based mobile application that it claims will help businesses save energy and therefore money. The mobile app offers businesses the ability to quickly calculate potential energy savings that can be achieved by installing high-efficiency electric motors and drives solutions.
Pierre Makinsky, Strategic Planner at Emerson Industrial Automation, explains that the app takes account of the application in its entirety, rapidly running simulations and comparing the existing equipment according to different scenarios. Potential savings for the application concerned are calculated and displayed in the form of a graphic overview.
Makinsky: “This tool is enabling our customers to identify very quickly, smoothly and easily how much they can save, how many KWh per year they can save, on their electric motor-based industrial applications.”
The app may also be used to transmit the result of a simulation directly to Emerson for more in-depth analysis. As Makinsky notes: “There are usually a lot of ways to address and think about how to optimise energy consumption, even for simple applications and what the tool enables us to do with the customer is to define different scenarios based on different technologies.”
He continues: “For an electric motor over 20 years, the total cost of ownership is made of 2%-4% based on initial investment, then 90%-95% made of electricity consumption. The tool enables our engineers, together with the customer, to optimise the duty cycle as well.”
Again, Makinsky highlights the need for clear visualisation: “This tool helps us to speak to the key decision-makers in our customer’s company and help them make the best informed decision based on their financial requirements.”
He cites an example of a ventilation application: “For some customer, the best solution will be simply to add a variable speed drive as it might be providing the shortest payback period. For others more interested in the long term benefits, the best solution might be to replace as well the motor by a super-premium efficiency motor and to optimize the design of the application to remove the transmission. This might effectively results in the lowest Total Cost of Ownership (TCO) over the life of the equipment”
Found in the cloud
As the Emerson app reveals, key to effective use of large volumes of data is more than simply gathering the information, it also relies on timely processing of that data in order to draw valid conclusions.
Gibbels explains: “In order to really facilitate its use it’s not just about what you do with the data but can you also in a reasonable timeframe crunch this data. To facilitate that you need a cloud-enabled platform, otherwise you have to go back to the old days where you’d look at mainframes and so it wouldn’t really be feasible or scalable. Analytics is one part, but also how do you facilitate and give it the necessary speed to work with this information is critical.”
Outsourcing on-site or on-premises data crunching to data centres enabled by a cloud-based operating system allows for different units to share this environment, avoiding the replication of a major installation on each site. But there are other benefits too.
Gibbels says: “To outsource this has many values, the value of performance within those data centres, it’s the security of the data, it’s the lower cost of using those systems, and you can always take advantage of the latest analytics and not rely on some manual upgrade or annual upgrade.”
Indeed, he argues that ‘software as a service’ has tremendous value. There are different models and scenarios available from a cloud perspective, but it’s a key requirement in order to take advantage of the strength around big data and analytics and to have it fully optimized and accessible from multiple sources, including mobile devices, Gibbels says.
A recent example comes from Ericsson, E.ON and ABB, which last year announced a cross-industry collaboration to develop smart energy solutions for a number of commercial sectors, including real estate and data centres. At the heart of the collaboration is data gathering, analysis and dissemination centred on the cloud.
Focused on Brunnshög, an area in Lund, Sweden, which plans to create a European model for sustainable urban planning, products created within the partnership will be launched through Brunnshög Energi AB, E.ON’s start-up innovation company. An initial pilot project is already underway focusing on the commercial real estate area to reduce operating costs through improved energy efficiency.
ABB’s building automation platform is delivering energy management functions, as well as gathering building data, which is securely providing meaningful data to Ericsson’s cloud-based service enablement platform.
Cecilia Berg, Ericsson’s Head of Industry and Society Sweden Accounts, Customer Unit (CU) Industry and Society, Region Northern Europe and Central Asia, says: “We are using our cloud solution when developing products for the commercial buildings. We are looking at the building and looking at the data that the building is generating with different sensors that are already there. So then we have a cloud solution or some sort of middleware that we connect the building information system to our cloud and then E.ON are developing apps for the building.”
Exploring the potential of big data
Data analysis can evidently yield operational advantages for individual machines and processes, but also offers some intriguing possibilities for more profound improvements in energy efficiency. As Gibbels explains: “Where it becomes really interesting is if you don’t just look at it from plant perspective but from a fleet perspective. Once you look at a fleet from the same or mixed energy source (i.e. gas, coal, wind, etc.) and start comparing, you have lessons learned from each plant, regardless of how they operate in different market conditions.”
For example, he suggests considering a potential failure at one site could enable preventative strategies to be put in place at other sites. “There are all kinds of scenarios you can think of to make those kinds of comparisons or analysis, and this is again where big data comes in,” he says, adding: “The data is not just there to monitor, as it was traditionally, but also that’s where the key value comes in to constantly make suggestions on how to optimise the plant. You can have various ‘what if’ scenarios.”
Considering one approach from GE, Gibbels refers to the ‘digital twin’ – a representation in a digital format of the physical plant environment. “You constantly can make predictive assumptions, looking forward before it happens in the physical environment. The power of all this really comes together to have that insight and be even more proactive than we currently can do.”
Indeed, GE recently set up a $1 billion clean energy consultancy, ‘Current’, in a move it says will transform the energy sector. Using its proprietary software to analyse energy consumption and provide customers recommendations to increase efficiency, GE says Current will help customers save an estimated 10%-20% on their energy bills.
There is evidently a clear trend toward increasing connectivity via the industrial internet and with it ever greater volumes of data. The use of this data in an effective and timely manner to enable informed business decisions is a key route to increasing energy efficiency and with it corporate competiveness. But fundamentally, this is not some far-flung future vision. The systems – cloud, analytics, big data – all these things are in place at a cost-effective scale. Now is the time to get connected.